Least squares based estimation of synchronous generator states and parameters with phasor measurement units

Authors: Yasser Wehbe, Lingling Fan, Zhixin Miao

Publication date: 2012/9/9

Conference name: North American Power Symposium (NAPS), 2012

Pages: 1-6

Publisher: IEEE

Link:  Least squares based estimation of synchronous generator states and parameters with phasor measurement units

Abstract: 

This paper investigates the estimation of synchronous generator states and parameters related to angular stability using PMU data. The method proposed in this paper uses finite difference technique and least squares method to evaluate differential equations governing the synchronous machine using a time window of PMU measurements. Sensitivity studies have been carried out to evaluate the impact of system strength, transmission line length, machine controls (exciter and governor) and local load on estimation accuracy. The simulation studies demonstrate the feasibility of the proposed method in dynamic states and parameters estimation.

UKF based estimation of synchronous generator electromechanical parameters from phasor measurements

Title

Authors: Yasser Wehbe, Lingling Fan

Publication date: 2012/9/9

Conference name: North American Power Symposium (NAPS), 2012

Publisher: IEEE

Link: UKF based estimation of synchronous generator electromechanical parameters from phasor measurements

Abstract:

The paper proposes an Unscented Kalman Filter (UKF)-based algorithm to estimate the electromechanical parameters and states of synchronous machines (rotor angle, q-axis reactance, inertia, damping and mechanical power). The algorithm uses observations or measurements available at the output terminal of the machine polluted by colored noise. Testing of the algorithm was conducted against a model of the same complexity and a model of a higher complexity. The contribution of this paper is twofold: 1) the algorithm is able to estimate electromechanical parameters such as inertia H and damping D which have not been investigated in other machine estimation papers. Modeling error is modeled as colored noise to enhance the estimation capability; and 2) a dual UKF filter is set up to carry out the estimation where the estimator of q-axis reactance is separated from the other states and parameters. Such set up solves the difficulty of UKF based estimation. Two case studies demonstrate the feasibility of the estimation.